Systems and methods for on-screen graphics detection

ABSTRACT

A system and method is disclosed for detecting locally-generated or other unknown graphics that are superimposed on a video program displayed on a television receiver or other like device. Devices external to a television receiver, such as a cable or satellite set-top box, can generate logos, electronic program guides, or other images that are then graphically overlaid on the television signal emanating from the device to the television&#39;s display. The system and method described herein provides a means to detect the presence of such on-screen graphics both to detect and identify graphical information and to also enable automated resolution of any interference among or between a plurality of video graphic sub-systems.

PRIORITY CLAIM

This application constitutes a continuation-in-part of U.S. patentapplication Ser. No. 12/788,721, entitled “METHODS FOR IDENTIFYING VIDEOSEGMENTS AND DISPLAYING CONTEXTUAL TARGETED CONTENT ON A CONNECTEDTELEVISION,” filed May 27, 2010, and issued Nov. 6, 2013 as U.S. Pat.No. 8,595,781, that application being a non-provisional applicationclaiming priority from U.S. Provisional Patent Application No.61/182,334, entitled “SYSTEM FOR PROCESSING CONTENT INFORMATION IN ATELEVIDEO SIGNAL,” filed May 29, 2009 and being a non-provisionalapplication claiming priority from U.S. Provisional Patent ApplicationNo. 61/290,714, entitled “CONTEXTUAL TARGETING BASED ON DATA RECEIVEDFROM A TELEVISION SYSTEM,” filed Dec. 29, 2009; this application furtherconstitutes a continuation-in-part of U.S. patent application Ser. No.12/788,748, entitled “METHODS FOR DISPLAYING CONTEXTUALLY TARGETEDCONTENT ON A CONNECTED TELEVISION,” filed May 27, 2010; this applicationfurther constitutes a continuation-in-part of U.S. patent applicationSer. No. 14/089,003, entitled “METHODS FOR IDENTIFYING VIDEO SEGMENTSAND DISPLAYING CONTEXTUALLY TARGETED CONTENT ON A CONNECTED TELEVISION,”filed Nov. 25, 2013; this application further constitutes acontinuation-in-part of U.S. patent application Ser. No. 14/217,039,entitled “SYSTEMS AND METHODS FOR ADDRESSING A MEDIA DATABASE USINGDISTANCE ASSOCIATIVE HASHING,” filed Mar. 17, 2014; this applicationfurther constitutes a continuation-in-part of U.S. patent applicationSer. No. 14/217,075, entitled “SYSTEMS AND METHODS FOR IDENTIFYING VIDEOSEGMENTS FOR DISPLAYING CONTEXTUALLY RELEVANT CONTENT,” filed Mar. 17,2014; this application further constitutes a continuation-in-part ofU.S. patent application Ser. No. 14/217,094, entitled “SYSTEMS ANDMETHODS FOR REAL-TIME TELEVISION AD DETECTION USING AN AUTOMATED CONTENTRECOGNITION DATABASE,” filed Mar. 17, 2014; this application furtherconstitutes a continuation-in-part of U.S. patent application Ser. No.14/217,425, entitled “SYSTEMS AND METHODS FOR IMPROVING SERVER ANDCLIENT PERFORMANCE IN FINGERPRINT ACR SYSTEMS,” filed Mar. 17, 2014;this application further constitutes a continuation-in-part of U.S.patent application Ser. No. 14/217,435, entitled “SYSTEMS AND METHODSFOR MULTI-BROADCAST DIFFERENTIATION,” filed Mar. 17, 2014; and thisapplication further constitutes a non-provisional application of U.S.Provisional Patent Application No. 61/791,578, entitled “SYSTEMS ANDMETHODS FOR IDENTIFYING VIDEO SEGMENTS BEING DISPLAYED ON REMOTELYLOCATED TELEVISIONS,” filed Mar. 15, 2013. The foregoing applicationsare either currently co-pending or are applications of which a currentlyco-pending application is entitled to the benefit of the filing date andare hereby incorporated by reference in their entirety as if fully setforth herein.

FIELD OF THE INVENTION

This invention generally relates to image recognition, and moreparticularly, to systems and methods for on-screen graphics detection.

BACKGROUND

A system and method is disclosed for detecting locally-generated orother unknown graphics that are superimposed on a video programdisplayed on a television receiver or other like device. Devicesexternal to a television receiver, such as a cable or satellite set-topbox, can generate logos, electronic program guides, or other images thatare then graphically overlaid on the television signal emanating fromthe device to the television's display. Likewise, the new generation ofsmart TV's contain internal processors and graphics display means todisplay overlaid windows of information generated by smartphone-likeapplications on said internal processors. Said internal processing canalso receive television programming from the Internet and display saidprogramming in place of television program from traditional televisionbroadcasters. Further, local broadcast or cable TV operators can overlaycertain graphics or alerts superimposed on the television programmingthat they carry. In some instances, understanding what the graphicscommunicate is important such as programmer identification. In othercases, these graphics can result in impairing or disabling the videorecognition capability of an automatic content recognition (ACR) system[such as with the invention of U.S. Pat. No. 8,595,781 of which thisdocument is a continuation in part]. The system and method describedherein provides a means to detect the presence of such on-screengraphics both to detect and identify graphical information and to alsoenable automated resolution of any interference among or between aplurality of video graphic sub-systems.

Television broadcast signals have long included static graphics such aslogos, program identification, or other information formatted to displaysuperimposed on underlying video programming. Often, these identifiersare small in size, semi-transparent and located in a corner of thedisplay area. A common example is the logo of a broadcast networkdisplayed in typically the lower right corner of a television picture.In recent decades, information about the television programing, such asthe network, channel and the name of the program, has been embedded asmetadata in the digital television signal and broadcast freely totelevision receivers. In other cases, television program information hasbeen supplied from third-parties such as Tribune and Rovi as electronicprogram guides (EPG). This information can be formatted as graphicalinformation for display on television receivers by cable and satelliteset-top boxes.

Television sets, set-top boxes, and home computers are now converginginto what are sometimes called “Smart TVs.” To take advantage of thefull potential of this new technology, the computing means within orassociated with the television set needs real-time “awareness” of theprograming being displayed by it.

Various means to achieve that goal of such content awareness are knownto those skilled in the art; including approaches to videofingerprinting that enable a computing means to match what is currentlybeing displayed on the screen of the television to databases of possiblecandidates. A typical system that possesses this capability is describedin U.S. Pat. No. 8,595,781.

However, a difficulty arises when additional, local components (such asa set-top box, game console or other connected devices) generategraphical user interfaces, text messages, or logos that displaysuperimposed on the video programming. This overlaying of graphicalelements, such as program information that the user has invoked from acable or satellite set-top box, cause the video fingerprint recognitionmeans to fail since the fingerprint matching data provided for thealgorithm has no awareness of the additional locally-generated graphicalscreen elements and may return a “no match” result. It is the goal ofthis invention to enable the video matching sub-system to associate anysuch “no match” result with an “on-screen graphic interference”notification to enable the video matching system to respondappropriately. It is also a goal of the system operating on theprocessing means within a television system to signal information to acentral content matching system to adjust to the presence of otherwiseinterfering graphical elements and only attempt to match video samplesdrawn from around the video display in areas not affected by locallygenerated graphic elements. It is still a further goal of the inventionto identify overlaid graphical elements, such as television channellogos, using the processing means of the smart TV when advantageous tothe system.

SUMMARY

In some embodiments, an exemplary method related to on-screen graphicsdetection may include detecting one or more graphics superimposed over acontent rendered on a display of a television; and providing at leastsome data associated with the detected one or more graphics to at leastone content recognition operation configured for at least determiningone or more identifiers associated with the content being rendered.

In some embodiments, detecting one or more graphics superimposed on acontent rendered on a television display may include detecting at leastone graphic superimposed over the content by at least one of controllogic associated with the television, an external device operativelycoupled with the television, an original broadcaster of the content, orat least one of a local broadcast or cable TV operator retransmittingthe content. In some embodiments, detecting one or more graphicssuperimposed on a content rendered on a television display may includedetecting one or more at least partially opaque graphics superimposedover a content rendered on a display of a television. In someembodiments, detecting one or more graphics superimposed on a contentrendered on a television display may include detecting one or more of atleast one banner superimposed over a content, at least one watermarksuperimposed over a content, at least one logo superimposed over acontent, or at least one identifier related to a content rendered in atleast one of HDTV or SDTV.

In some embodiments, detecting one or more graphics superimposed over acontent rendered on a display of a television may include detecting oneor more of at least some program guide information, at least a portionof a graphical user interface, at least some program identificationinformation, at least some text, or at least some image that is notassociated with original program content or underlying videoprogramming.

In some embodiments, detecting one or more graphics superimposed over acontent rendered on a display of a television may include detecting oneor more high contrast differences between video sections of a contentrendered on a display of a television. In some embodiments, detectingone or more graphics superimposed over a content rendered on a displayof a television may include detecting one or more graphics superimposedover a content, including at least one identification of one or more ofat least one horizontal edge, at least one vertical edge, at least onediagonal edge, or at least one corner associated with the contentrendered on the display.

In some embodiments, detecting one or more graphics superimposed over acontent, including at least one identification of one or more of atleast one horizontal edge, at least one vertical edge, at least onediagonal edge, or at least one corner associated with the contentrendered on the display may include determining one or more pixel patchlocations and one or more pixel patch sizes corresponding with the oneor more pixel patch locations; sampling at least some pixel dataassociated with the content rendered on the display, the samplingoccurring at the one or more determined pixel patch locations;transforming the at least some pixel data sampled from the one or moredetermined pixel patch locations; and identifying one or more of atleast one horizontal edge, at least one vertical edge, at least onediagonal edge, or at least one corner associated with the contentrendered on the display based at least partially on at least a portionof the transformed at least some pixel data from at least one sampledpixel patch.

In some embodiments, detecting one or more graphics superimposed over acontent, including at least one identification of one or more of atleast one horizontal edge, at least one vertical edge, at least onediagonal edge, or at least one corner associated with the contentrendered on the display may further include identifying one or more ofat least one additional horizontal edge, at least one additionalvertical edge, or at least one additional corner based at leastpartially on at least a portion of the transformed at least some pixeldata from at least one other sampled pixel patch. In some embodiments,detecting one or more graphics superimposed over a content, including atleast one identification of one or more of at least one horizontal edge,at least one vertical edge, at least one diagonal edge, or at least onecorner associated with the content rendered on the display may furtherinclude identifying one or more of at least one additional horizontaledge, at least one additional vertical edge, or at least one additionalcorner based at least partially on one or more stepwise sweepoperations, wherein a stepwise sweep operation is configured forexamining successive pixel patch locations in at least one of ahorizontal or vertical direction starting from a pixel patch locationassociated with the identified one or more of at least one horizontaledge, at least one vertical edge, or at least one corner.

In some embodiments, sampling at least some pixel data associated withthe content rendered on the display, the sampling occurring at the oneor more determined pixel patch locations and transforming the at leastsome pixel data sampled from the one or more determined pixel patchlocations may include storing the content rendered on the display in oneor more buffers; removing color data associated with the content fromthe one or more buffers; performing at least one Gaussian blur operationon the data in the one or more buffers; and transforming data associatedwith the one or more pixel patch locations and the one or more buffersto identify one or more high-contrast regions of pixel patches, the oneor more high-contrast regions at least partially determinative of one ormore of at least one horizontal edge, at least one vertical edge, atleast one diagonal edge, or at least one corner associated with thecontent rendered on the display.

In some embodiments, transforming data associated with the one or morepixel patch locations and the one or more buffers to identify one ormore high-contrast regions of pixel patches, the one or morehigh-contrast regions at least partially determinative of one or more ofat least one horizontal edge, at least one vertical edge, at least onediagonal edge, or at least one corner associated with the contentrendered on the display may include transforming data associated withthe one or more pixel patch locations and the one or more buffers usingat least one of a discrete cosine transform, a Sobel algorithm, a Shanalgorithm, or another algorithm operable to identify one or morehigh-contrast regions of pixel patches.

In some embodiments, determining one or more pixel patch locations andone or more pixel patch sizes corresponding with the one or more pixelpatch locations may include determining one or more pixel patchlocations and one or more pixel patch sizes corresponding with the oneor more pixel patch locations based at least partially on at least onedetermination of a resolution associated with the content rendered onthe display.

In some embodiments, an exemplary computer program product related toon-screen graphics detection may include at least one non-transitorycomputer-readable medium, and the at least one non-transitorycomputer-readable medium may include one or more instructions fordetecting one or more graphics superimposed over a content rendered on adisplay of a television; and one or more instructions for providing atleast some data associated with the detected one or more graphics to atleast one content recognition operation configured for at leastdetermining one or more identifiers associated with the content beingrendered.

In some embodiments, an exemplary system related to on-screen graphicsdetection may include circuitry configured for detecting one or moregraphics superimposed over a content rendered on a display of atelevision; and circuitry configured for providing at least some dataassociated with one or more detected graphics to at least one contentrecognition operation configured for at least determining one or moreidentifiers associated with content being rendered.

In addition to the foregoing, various other methods, systems and/orprogram product embodiments are set forth and described in the teachingssuch as the text (e.g., claims, drawings and/or the detaileddescription) and/or drawings of the present disclosure.

The foregoing is a summary and thus contains, by necessity,simplifications, generalizations and omissions of detail; consequently,those skilled in the art will appreciate that the summary isillustrative only and is NOT intended to be in any way limiting. Otheraspects, embodiments, features and advantages of the device and/orprocesses and/or other subject matter described herein will becomeapparent in the teachings set forth herein.

BRIEF DESCRIPTION OF THE DRAWINGS

Certain embodiments of the present invention are described in detailbelow with reference to the following drawings:

FIG. 1 illustrates the sampling of the raster of a typical televisionscreen 101 with a number of “pixel patches” 103. As taught by theinvention of which this is a continuation in part, the processing meanswithin the television is instructed to sample the video display memoryin only certain locations (eight locations are used in this example) andto apply certain algorithmic processes to said pixel patches. Theresults of said processes are transmitted to a central server means at aprogrammable rate such as every video frame or every other video frame,etc.

FIG. 2 shows a graphic overlay 205 conveying current program informationthat is formatted along the bottom edge of the screen so pixel patchesin that area will change from the values in the central referencedatabase while overlaid.

FIGS. 3 and 4 illustrate another sampling scheme where alocally-generated banner is detected and sized by finding its corners304 and looking for what patches remain relatively constant, as comparedto normal video of a television program.

FIG. 5 illustrates detecting 508 whether the display is formatted as 507standard definition or as HDTV, 505 and 506.

FIG. 6 shows an example video frame showing television programmingoverlaid with an information banner.

FIG. 7 shows an example video frame after processing with filterequation 703 to reveal horizontal boundaries.

FIG. 8 shows an example video frame after processing with filterequation 803 to reveal vertical boundaries.

FIG. 9 shows an example video frame after processing with both filterequations for FIGS. 7 & 8 revealing horizontal & vertical edgeboundaries.

FIG. 10 illustrates sampling in the four corners of a video frame todetect an on screen logo 1003 with a pixel patch array 1004.

FIG. 11 illustrates sampling method searching for edges and distancesbetween reference image of a typical television network logo and a logofound in the corner of a video frame.

FIG. 12 shows an example of a DCT macro block encoding a region of 8 by8 pixels containing high-frequency content which could be an edge orcorner of a graphic element.

FIG. 13 illustrates an operational flow representing example operationsrelated to on-screen graphics detection.

FIG. 14 illustrates an alternative embodiment of the operational flow ofFIG. 13.

FIG. 15 illustrates an alternative embodiment of the operational flow ofFIG. 13.

FIG. 16 illustrates an alternative embodiment of the operational flow ofFIG. 13.

FIG. 17 illustrates an alternative embodiment of the operational flow ofFIG. 13.

FIG. 18 illustrates an alternative embodiment of the operational flow ofFIG. 13.

FIG. 19 illustrates an alternative embodiment of the operational flow ofFIG. 13.

FIG. 20 illustrates an alternative embodiment of the operational flow ofFIG. 13.

FIG. 21 illustrates an alternative embodiment of the operational flow ofFIG. 13.

FIG. 22 illustrates an alternative embodiment of the operational flow ofFIG. 13.

FIG. 23 illustrates an alternative embodiment of the operational flow ofFIG. 13.

FIG. 24 illustrates an alternative embodiment of the operational flow ofFIG. 13.

FIG. 25 illustrates an exemplary computer program product related toon-screen graphics detection.

FIG. 26 illustrates a system related to on-screen graphics detection.

DETAILED DESCRIPTION

One means of graphic overlay detection is to use an algorithm to findvideo image edges by detecting high contrast differences between videosections of a television raster. Such algorithmic means are well knownto the person skilled in the art. If said transition area remains in anexpected locations for longer than a short duration, such as a programinformation banner overlay, then the likelihood of detecting said bannerusing the means of this system and method is high.

A “pixel patch” is defined as a block of pixels that are sampled fromthe raster. For the purposes of graphics overlay detection, such pixelpatches might be sized to 32 by 32, or a multiple thereof such as 64 by64 to take advantage of the discrete cosine transform or DCT. The DCTfunction can be readily performed internally to the television monitor101 by the television's internal processor means using the softwareapplication of the invention. The sharp edges of a graphic overlay 205can be detected by examining the coefficients in the lower rightquadrant of the DCT transform of each macro block regardless of sizechosen.

The detection process could also include detecting over a predeterminedlength of time unchanging high frequency information from the same DCTtransform location to confirm the presence of a graphic overlay. In thismanner, the scrolling banners frequently seen in news programs would nottrigger the overlay detection as the moving text of the banner would bereadily detected by the changing DCT coefficients.

Likewise, a method can be employed using algorithms such as Sobel andSharr or using similar means as taught by the open-source perceptualhashing family of image analysis. As with the DCT method above, thesealgorithmic means also can be used to detect edges, as well as corners,of graphical objects within video signals. Similar to each of these saidmeans, an odd dimensioned matrix such as 3×3 pixels is used in aconvolution-coded stepwise sweep over a video area of interest to searchfor edges.

The process begins with reducing the pixel information of an RGB valueof 8 bits each (16 million colors) to an eight-bit monochrome value.Next, a Gaussian blur is applied to reduce noise in the videoinformation. Next the pixel matrix, in this example 3 by 3, is passedover the video area of interest. This matrix calculated the first-orderdifferential of the pixel values relative to either the vertical orhorizontal axis of the video raster. The computed differential is leftbehind in the respective pixel locations which can then be easilyexamined for maximum values indicating edges as seen in FIG. 8.

Another means of detecting graphics overlays is by “training” the systemof the invention with the image of one or more graphics overlay to bedetected using an image matching algorithmic approach such as perceptualhash (pHash), a public domain algorithm well known to those skilled inthe art. Other video frame comparison algorithm might include theScale-invariant feature transform (SIFT) or Speeded Up Robust Features(SURF) both of which are also well known to one skilled in the art.

Assuming the use of pHash, entire video frames are quickly processed bythe pHash algorithm and the resulting hash values are may be compared tothe reference video images, also processed by pHash means but suppliedfrom the central server means of the invention via the datacommunications link with the application process of the inventionresident in the television system. One of the advantages of using pHashis its ability to reliably match coarse features such as largerectangles or other shapes of graphic overlays with relatively highinsensitivity to contrast, brightness or color changes. Anotheradvantage is its ability to also match detailed individual video frames.

A further improvement of the invention would be to maintain anappropriately sized library of different possible graphics overlaycomparison candidates while still reducing the number of total imagesearches per unit of time. This is done based on past successfuldetections such that the most probably graphics overlays are tested morefrequently than overlays that have yet to be detected. The process ofdetecting graphics overlay presence need only be applied at a rate lessthan that of the first invention [to which this is a CIP] and,regardless of the means described above, the graphics overlay detectionprocess can easily be interleaved in the television application processwith the normal automated content recognition processes of the firstinvention.

In FIG. 3, pixel patches 11, 12, 13, 16, 17 & 18 are used for edgedetection using the discrete cosine transform (DCT) instead of beingapplied to the normal search means of the invention (as described in themain patent application.) FIG. 4 illustrates a similar pattern foroverlay detection for large overlays such as electronic program guides.In this figure, pixel patch 1, 2, 3, 16, 17 & 18 may be all that need tobe tested for accurate overlay detection.

There are a variety of considerations that determine how to detect apatch pattern. Logo detection, speed of detection, accuracy ofdetection, channel banners, HD content, SD content, FIG. 5. Thisinvention uses pixel pattern detection in known areas of a televisiondisplay raster to find matches to television broadcast logos to identifyprogram channels. As with the previously defined graphics overlaydetection, the invention might employ perceptual hashing algorithmswhere pHash processed reference images of all television logos ofinterest are supplied by the central server means of the invention tothe television application of the invention. Said television applicationthen periodically tests the video raster for matches of logos or othergraphics elements of interest by continuously cycling through thelibrary of supplied reference images from the central server. Thisprocess is periodically performed and interspersed with saidapplications normal duties of harvesting pixel patches for the primaryautomated content recognition function of the invention.

FIG. 5 illustrates a further aspect of the invention using pixel patches1, 6, 11, 16 of the left column and 3, 8, 13, 18 of the right column todetect changing video only in the presence of HDTV picture informationand hence can provide a means to detect standard definition televisionwhen said pixel patches detect unchanging video. Said process need on beperformed on a reduced schedule from the normal video segment matchingduties of the invention. A simple test of dark or solid color equallydetected by the two columns of pixel patches would be sufficient toproduce a reliable indication of display mode between standard andhigh-definition.

Core ingest system match process description

1. Incoming video goes into TV Program DB

2. Incoming video is tested against TV Ad DB

3. If a match is found; TV ad segment is removed from TV Program DB

4. Go back to step 1.

5. Incoming video is tested against TV Program DB

6. If a match is found; TV ad segment is removed from TV Program DB andplaced in TV Ad DB

7. Go back to step 1.

Ad match process description

1. Test incoming video with normal threshold (of U.S. Pat. No.8,585,781) illustrated in 104 of FIG. 1 and segment is of length ofinterest (e.g. −5 seconds to 120 seconds)

2. If match, then retest at high threshold, illustrated in 105 of FIG. 1

3. If match, then retest at loose threshold but tight time tolerance

FIG. 13 illustrates an operational flow 1300 representing exampleoperations related to on-screen graphics detection. In FIG. 13 and infollowing figures that include various examples of operational flows,discussion and explanation may be provided with respect to theabove-described examples of FIGS. 1 through 12, and/or with respect toother examples and contexts. However, it should be understood that theoperational flows may be executed in a number of other environments andcontexts, and/or in modified versions of FIGS. 1 through 12. Also,although the various operational flows are presented in the sequence(s)illustrated, it should be understood that the various operations may beperformed in other orders than those which are illustrated, or may beperformed concurrently.

After a start operation, the operational flow 1300 moves to operation1302. Operation 1302 depicts detecting one or more graphics superimposedover a content rendered on a display of a television. For example, asshown in and/or described with respect to FIGS. 1 through 12.

Then, operation 1304 depicts providing at least some data associatedwith the detected one or more graphics to at least one contentrecognition operation configured for at least determining one or moreidentifiers associated with the content being rendered. For example, asshown in and/or described with respect to FIGS. 1 through 12.

FIG. 14 illustrates alternative embodiments of the example operationalflow 1300 of FIG. 13. FIG. 14 illustrates an example embodiment whereoperation 1302 may include at least one additional operation. Additionaloperations may include operation 1402, operation 1404, and/or operation1406.

Operation 1402 illustrates detecting at least one graphic superimposedover the content by at least one of control logic associated with thetelevision, an external device operatively coupled with the television,an original broadcaster of the content, or at least one of a localbroadcast or cable TV operator retransmitting the content. For example,as shown in and/or described with respect to FIGS. 1 through 12.

Further, operation 1404 illustrates detecting one or more at leastpartially opaque graphics superimposed over a content rendered on adisplay of a television. For example, as shown in and/or described withrespect to FIGS. 1 through 12.

Further, operation 1406 illustrates detecting one or more of at leastone banner superimposed over a content, at least one watermarksuperimposed over a content, at least one logo superimposed over acontent, or at least one identifier related to a content rendered in atleast one of HDTV or SDTV. For example, as shown in and/or describedwith respect to FIGS. 1 through 12.

FIG. 15 illustrates alternative embodiments of the example operationalflow 1300 of FIG. 13. FIG. 15 illustrates an example embodiment whereoperation 1302 may include at least one additional operation. Additionaloperations may include operation 1502, operation 1504, and/or operation1506.

Operation 1502 illustrates detecting one or more of at least someprogram guide information, at least a portion of a graphical userinterface, at least some program identification information, at leastsome text, or at least some image that is not associated with originalprogram content or underlying video programming. For example, as shownin and/or described with respect to FIGS. 1 through 12.

Further, operation 1504 illustrates detecting one or more high contrastdifferences between video sections of a content rendered on a display ofa television. For example, as shown in and/or described with respect toFIGS. 1 through 12.

Further, operation 1506 illustrates detecting one or more graphicssuperimposed over a content, including at least one identification ofone or more of at least one horizontal edge, at least one vertical edge,at least one diagonal edge, or at least one corner associated with thecontent rendered on the display. For example, as shown in and/ordescribed with respect to FIGS. 1 through 12.

FIG. 16 illustrates alternate embodiments of the example operationalflow 1300 of FIG. 13. FIG. 16 illustrates an example embodiment whereoperation 1506 may include at least one additional operation. Additionaloperations may include operation 1602, 1604, 1606, 1608, 1610, 1612,and/or 1614.

Operation 1602 illustrates determining one or more pixel patch locationsand one or more pixel patch sizes corresponding with the one or morepixel patch locations. For example, as shown in and/or described withrespect to FIGS. 1 through 12.

Operation 1604 illustrates sampling at least some pixel data associatedwith the content rendered on the display, the sampling occurring at theone or more determined pixel patch locations. For example, as shown inand/or described with respect to FIGS. 1 through 12.

Operation 1606 illustrates transforming the at least some pixel datasampled from the one or more determined pixel patch locations. Forexample, as shown in and/or described with respect to FIGS. 1 through12.

Operation 1608 illustrates identifying one or more of at least onehorizontal edge, at least one vertical edge, at least one diagonal edge,or at least one corner associated with the content rendered on thedisplay based at least partially on at least a portion of thetransformed at least some pixel data from at least one sampled pixelpatch. For example, as shown in and/or described with respect to FIGS. 1through 12.

Operation 1610 illustrates identifying one or more of at least oneadditional horizontal edge, at least one additional vertical edge, or atleast one additional corner based at least partially on at least aportion of the transformed at least some pixel data from at least oneother sampled pixel patch. For example, as shown in and/or describedwith respect to FIGS. 1 through 12.

Operation 1612 illustrates identifying one or more of at least oneadditional horizontal edge, at least one additional vertical edge, or atleast one additional corner based at least partially on one or morestepwise sweep operations, wherein a stepwise sweep operation isconfigured for examining successive pixel patch locations in at leastone of a horizontal or vertical direction starting from a pixel patchlocation associated with the identified one or more of at least onehorizontal edge, at least one vertical edge, or at least one corner. Forexample, as shown in and/or described with respect to FIGS. 1 through12.

Operation 1614 illustrates determining one or more pixel patch locationsand one or more pixel patch sizes corresponding with the one or morepixel patch locations based at least partially on at least onedetermination of a resolution associated with the content rendered onthe display. For example, as shown in and/or described with respect toFIGS. 1 through 12.

FIG. 17 illustrates alternate embodiments of the example operationalflow 1300 of FIG. 13. FIG. 17 illustrates an example embodiment whereoperation 1604 may include at least one additional operation. Additionaloperations may include operation 1702, 1704, 1706, 1708, and/or 1710.

Operation 1702 illustrates storing the content rendered on the displayin one or more buffers. For example, as shown in and/or described withrespect to FIGS. 1 through 12.

Operation 1704 illustrates removing color data associated with thecontent from the one or more buffers. For example, as shown in and/ordescribed with respect to FIGS. 1 through 12.

Operation 1706 illustrates performing at least one Gaussian bluroperation on the data in the one or more buffers. For example, as shownin and/or described with respect to FIGS. 1 through 12.

Operation 1708 illustrates transforming data associated with the one ormore pixel patch locations and the one or more buffers to identify oneor more high-contrast regions of pixel patches, the one or morehigh-contrast regions at least partially determinative of one or more ofat least one horizontal edge, at least one vertical edge, at least onediagonal edge, or at least one corner associated with the contentrendered on the display. For example, as shown in and/or described withrespect to FIGS. 1 through 12.

Operation 1710 illustrates transforming data associated with the one ormore pixel patch locations and the one or more buffers using at leastone of a discrete cosine transform, a Sobel algorithm, a Sharralgorithm, or another algorithm operable to identify one or morehigh-contrast regions of pixel patches. For example, as shown in and/ordescribed with respect to FIGS. 1 through 12.

FIG. 18 illustrates alternate embodiments of the example operationalflow 1300 of FIG. 13. FIG. 18 illustrates an example embodiment whereoperation 1302 may include at least one additional operation. Additionaloperations may include operation 1802, 1804, 1806, 1808, 1810, and/or1812.

Operation 1802 illustrates determining one or more pixel patch locationsand one or more pixel patch sizes corresponding with the one or morepixel patch locations. For example, as shown in and/or described withrespect to FIGS. 1 through 12.

Operation 1804 illustrates sampling at a first time at least some pixeldata associated with the content rendered on the display, the samplingoccurring at the one or more determined pixel patch locations. Forexample, as shown in and/or described with respect to FIGS. 1 through12.

Operation 1806 illustrates sampling at a second time at least some pixeldata associated with the content rendered on the display, the samplingoccurring at the one or more determined pixel patch locations. Forexample, as shown in and/or described with respect to FIGS. 1 through12.

Operation 1808 illustrates establishing that at least one pixel patch isat least substantially the same at both the first sample and the secondsample and establishing that at least one pixel patch substantiallydiffers at the first sample and the second sample. For example, as shownin and/or described with respect to FIGS. 1 through 12.

Operation 1810 illustrates determining one or more pixel patch locationsand one or more pixel patch sizes corresponding with the one or morepixel patch locations based at least partially on at least onedetermination of a resolution associated with the content rendered onthe display. For example, as shown in and/or described with respect toFIGS. 1 through 12.

Operation 1812 illustrates at least one of (i) establishing that atleast one pixel patch is the same at both the first sample and thesecond sample or (ii) establishing that at least a portion of the atleast one pixel patch associated with one or more at least partiallyopaque graphics is the same at both the first sample and the secondsample and establishing that an underlying portion of the at least onepixel patch may vary between the first sample and the second sample. Forexample, as shown in and/or described with respect to FIGS. 1 through12.

FIG. 19 illustrates alternate embodiments of the example operationalflow 1300 of FIG. 13. FIG. 19 illustrates an example embodiment whereoperation 1302 may include at least one additional operation. Additionaloperations may include operation 1902, 1904, 1906, 1908, 1910, 1912and/or 1914.

Operation 1902 illustrates determining, via at least some dataassociated with the detecting one or more graphics, a resolutionassociated with a content rendered on a display of a television. Forexample, as shown in and/or described with respect to FIGS. 1 through12.

Operation 1904 illustrates determining, via at least some dataassociated with the detecting one or more graphics, one or moreidentifiers associated with a content rendered on a display of atelevision in at least one of HDTV or SDTV. For example, as shown inand/or described with respect to FIGS. 1 through 12.

Operation 1906 illustrates determining one or more pixel patch locationsand one or more pixel patch sizes corresponding with the one or morepixel patch locations. For example, as shown in and/or described withrespect to FIGS. 1 through 12.

Operation 1908 illustrates sampling at a first time least some pixeldata associated with the content rendered on the display, the samplingoccurring at the one or more determined pixel patch locations. Forexample, as shown in and/or described with respect to FIGS. 1 through12.

Operation 1910 illustrates sampling at a second time at least some pixeldata associated with the content rendered on the display, the samplingoccurring at the one or more determined pixel patch locations. Forexample, as shown in and/or described with respect to FIGS. 1 through12.

Operation 1912 illustrates establishing that at least one pixel patchwithin at least a first proximity of at least one vertical boundary ofthe display is at least substantially the same at both the first sampleand the second sample and establishing that at least one pixel patchwithin at least a second proximity of a center of the display at leastsubstantially differs at the first sample and the second sample. Forexample, as shown in and/or described with respect to FIGS. 1 through12.

Operation 1914 illustrates at least one of (i) establishing that the atleast one pixel patch is the same at both the first sample and thesecond sample and (ii) establishing that the at least one pixel patch isassociated with at least one of a dark color or a solid color. Forexample, as shown in and/or described with respect to FIGS. 1 through12.

FIG. 20 illustrates alternate embodiments of the example operationalflow 1300 of FIG. 13. FIG. 20 illustrates an example embodiment whereoperation 1302 may include at least one additional operation. Additionaloperations may include operation 2002, 2004, 2006, 2008, 2010, 2012and/or 2014.

Operation 2002 illustrates receiving one or more indications of one ormore known graphics. For example, as shown in and/or described withrespect to FIGS. 1 through 12.

Operation 2004 illustrates detecting one or more graphics superimposedover a content rendered on a display of a television at least partiallybased on the received one or more indications of one or more knowngraphics. For example, as shown in and/or described with respect toFIGS. 1 through 12.

Operation 2006 illustrates receiving at least one of one (i) or moreindications associated with one or more previously recognized watermarksor logos or (ii) one or more indications associated with one or morebanners or one or more user interfaces implemented by one or moreconsumer electronic devices. For example, as shown in and/or describedwith respect to FIGS. 1 through 12.

Operation 2008 illustrates receiving the one or more indications at aclient, the receiving at least one of (i) at manufacture of the client,(ii) during a network update of the client, or (iii) during at least onecommunication between the client and a system configured for at leastdetermining one or more identifiers associated with the content beingrendered. For example, as shown in and/or described with respect toFIGS. 1 through 12.

Operation 2010 illustrates detecting via at least some pixel patterndetection within at least one proximity of one or more areas of atelevision display known to be associated with locations of the receivedone or more indications of one or more known graphics. For example, asshown in and/or described with respect to FIGS. 1 through 12.

Operation 2012 illustrates detecting via at least some pixel patterndetection within at least one proximity of at least one corner of thetelevision display. For example, as shown in and/or described withrespect to FIGS. 1 through 12.

Operation 2014 illustrates detecting via at least one of a pHashalgorithm, a Scale-invariant Feature Transform algorithm, or a SpeededUp Robust Features algorithm, one or more graphics superimposed over acontent rendered on a display of a television at least partially basedon the received one or more indications of one or more known graphics.For example, as shown in and/or described with respect to FIGS. 1through 12.

FIG. 21 illustrates alternate embodiments of the example operationalflow 1300 of FIG. 13. FIG. 21 illustrates an example embodiment whereoperation 2004 may include at least one additional operation, which mayinclude operation 2102.

Operation 2102 illustrates detecting one or more graphics superimposedover a content rendered on a display of a television at least partiallybased on the received one or more indications of one or more knowngraphics and based at least partially on at least one determination of aresolution associated with the content rendered on the display. Forexample, as shown in and/or described with respect to FIGS. 1 through12.

FIG. 22 illustrates alternate embodiments of the example operationalflow 1300 of FIG. 13. FIG. 22 illustrates an example embodiment whereoperation 1302 may include at least one additional operation. Additionaloperations may include operation 2202, and/or 2204. Further, operation1304 may include at least one additional operation. Additionaloperations may include operation 2206, and/or 2208.

Operation 2202 illustrates detecting one or more graphics superimposedover a content rendered on a display of a television at least one of asa part of a content recognition operation or following a previouscontent recognition operation. For example, as shown in and/or describedwith respect to FIGS. 1 through 12.

Operation 2204 illustrates detecting, by at least one of a widget of asmart television or a widget of a consumer device coupled with atelevision, one or more graphics superimposed over a rendered content.For example, as shown in and/or described with respect to FIGS. 1through 12.

Operation 2206 illustrates modifying at least one of one or more cues orone or more fingerprints operable to at least partially identify contentbeing rendered, the modifying based at least partially on detecting oneor more graphics superimposed over a content rendered on a display of atelevision. For example, as shown in and/or described with respect toFIGS. 1 through 12.

Operation 2208 illustrates providing at least some data operable toassociate at least one of a “no match” result or an “on-screen graphicinterference” notification with at least some cue or fingerprint databased at least partially on the detected one or more graphics. Forexample, as shown in and/or described with respect to FIGS. 1 through12.

FIG. 23 illustrates alternate embodiments of the example operationalflow 1300 of FIG. 13. FIG. 23 illustrates an example embodiment whereoperation 1304 may include at least one additional operation. Additionaloperations may include operation 2302, and/or 2304.

Operation 2302 illustrates providing one or more indications related toat least one of halting or resuming at least one process related toautomated content recognition based at least partially on at least oneof a detection of one or more graphics superimposed over a contentrendered on a display of a television or a detection of no graphicssuperimposed over a content rendered on a display of a television. Forexample, as shown in and/or described with respect to FIGS. 1 through12.

Operation 2304 illustrates providing the one or more indications to atleast one of a television, a client system operably coupled with atelevision, or a central system configured for at least determining oneor more identifiers associated with content being rendered on aplurality of clients. For example, as shown in and/or described withrespect to FIGS. 1 through 12.

FIG. 24 illustrates alternate embodiments of the example operationalflow 1300 of FIG. 13. FIG. 24 illustrates an example embodiment whereoperation 2206 may include at least one additional operation. Additionaloperations may include operation 2402, 2404, 2406, and/or 2408.

Operation 2402 illustrates providing at least some information relatedto at least one subset of pixel patches associated with an automatedcontent recognition operation, the automated content recognitionoperation based at least partially on a predefined number of pixelpatches. For example, as shown in and/or described with respect to FIGS.1 through 12.

Operation 2404 illustrates sending at least one indication to at leastone central system associated with the automated content recognitionoperation related to the at least one subset, the at least oneindication operable to cause the automated content recognition operationto attempt to recognize the content being rendered based at leastpartially on the at least one subset of pixel patches. For example, asshown in and/or described with respect to FIGS. 1 through 12.

Operation 2406 illustrates providing at least some information relatedto at least one alternate set of pixel patches associated with anautomated content recognition operation, the automated contentrecognition operation based at least partially on at least onepredefined number of pixel patches, wherein the at least one alternateset of pixel patches is determined based at least partially on thedetected one or more graphics. For example, as shown in and/or describedwith respect to FIGS. 1 through 12.

Operation 2408 illustrates sending at least one indication to at leastone central system associated with the automated content recognitionoperation related to the at least one subset, the at least oneindication operable to cause the automated content recognition operationto attempt to recognize the content being rendered based at leastpartially on the at least one alternate set of pixel patches. Forexample, as shown in and/or described with respect to FIGS. 1 through12.

FIG. 25 illustrates an exemplary computer program product 2500 which mayinclude at least one non-transitory computer-readable medium. Furtherillustrated in FIG. 25 are instructions 2502 of computer program product2500. Instructions 2502 illustrate one or more instructions fordetecting one or more graphics superimposed over a content rendered on adisplay of a television; and one or more instructions for providing atleast some data associated with the detected one or more graphics to atleast one content recognition operation configured for at leastdetermining one or more identifiers associated with the content beingrendered. For example, as shown in and/or described with respect toFIGS. 1 through 24, a computer program product may include one or moreinstructions encoded on and/or stored by one or more non-transitorycomputer-readable media. The one or more instructions may, when executedby one or more processing devices, cause the one or more processingdevices to perform operations including detecting one or more graphicssuperimposed over a content rendered on a display of a television; andproviding at least some data associated with the detected one or moregraphics to at least one content recognition operation configured for atleast determining one or more identifiers associated with the contentbeing rendered. The foregoing operations may be similar at least in partand/or be substantially similar to (but are not limited to)corresponding operations disclosed elsewhere herein.

FIG. 26 illustrates an exemplary system 2600. System 2600 may includecircuitry 2602, circuitry 2604, and/or circuitry 2606.

Circuitry 2602 illustrates circuitry configured for detecting one ormore graphics superimposed over a content rendered on a display of atelevision. For example, as shown in and/or described with respect toFIGS. 1 through 24, circuitry 2602 may cause operations with an effectsimilar at least in part and/or substantially similar to (but notlimited to) corresponding operations disclosed elsewhere herein.

Then, circuitry 2604 illustrates circuitry configured for providing atleast some data associated with one or more detected graphics to atleast one content recognition operation configured for at leastdetermining one or more identifiers associated with content beingrendered. For example, as shown in and/or described with respect toFIGS. 1 through 24, circuitry 2604 may cause operations with an effectsimilar at least in part and/or substantially similar to (but notlimited to) corresponding operations disclosed elsewhere herein.

The operations by which the video segment is determined may includeoperations described in a parent application, U.S. patent applicationSer. No. 12/788,721 (now U.S. Pat. No. 8,595,781), “METHODS FORIDENTIFYING VIDEO SEGMENTS AND DISPLAYING CONTEXTUAL TARGETED CONTENT ONA CONNECTED TELEVISION” (“the '781 patent”) and/or in related U.S.patent application Ser. No. 14/217,039, “SYSTEMS AND METHODS FORADDRESSING A MEDIA DATABASE USING DISTANCE ASSOCIATIVE HASHING” filedconcurrently with the instant application (“the related application”).perhaps via operations disclosed in the '781 patent and/or the relatedapplication.

The system and methods, flow diagrams, and structure block diagramsdescribed in this specification may be implemented in computerprocessing systems including program code comprising programinstructions that are executable by a computer processing system. Otherimplementations may also be used. Additionally, the flow diagrams andstructure block diagrams herein described describe particular methodsand/or corresponding acts in support of steps and correspondingfunctions in support of disclosed structural means, may also be utilizedto implement corresponding software structures and algorithms, andequivalents thereof

Embodiments of the subject matter described in this specification can beimplemented as one or more computer program products, i.e., one or moremodules of computer program instructions encoded on a tangible programcarrier for execution by, or to control the operation of, dataprocessing apparatus. The computer readable medium can be a machinereadable storage device, a machine readable storage substrate, a memorydevice, or a combination of one or more of them.

A computer program (also known as a program, software, softwareapplication, script, or code) can be written in any form of programminglanguage, including compiled or interpreted languages, or declarative orprocedural languages, and it can be deployed in any form, including as astand-alone program or as a module, component, subroutine, or other unitsuitable for use in a computing environment. A computer program does notnecessarily correspond to a file in a file system. A program can bestored in a portion of a file that holds other programs or data (e.g.,one or more scripts stored in a markup language document), in a singlefile dedicated to the program in question, or in multiple coordinatedfiles (e.g., files that store one or more modules, sub programs, orportions of code). A computer program can be deployed to be executed onone computer or on multiple computers that are located at one site ordistributed across multiple sites and interconnected by a suitablecommunication network.

The processes and logic flows described in this specification can beperformed by one or more programmable processors executing one or morecomputer programs to perform functions by operating on input data andgenerating output. The processes and logic flows can also be performedby, and apparatus can also be implemented as, special purpose logiccircuitry, e.g., an FPGA (field programmable gate array) or an ASIC(application specific integrated circuit).

The essential elements of a computer are a processor for performinginstructions and one or more memory devices for storing instructions anddata. Generally, a computer will also include, or be operatively coupledto receive data from or transfer data to, or both, one or more massstorage devices for storing data, e.g., magnetic, magneto optical disks,or optical disks. However, a computer need not have such devices.Processors suitable for the execution of a computer program include, byway of example only and without limitation, both general and specialpurpose microprocessors, and any one or more processors of any kind ofdigital computer. Generally, a processor will receive instructions anddata from a read only memory or a random access memory or both.

To provide for interaction with a user or manager of the systemdescribed herein, embodiments of the subject matter described in thisspecification can be implemented on a computer having a display device,e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor,for displaying information to the user and a keyboard and a pointingdevice, e.g., a mouse or a trackball, by which the user can provideinput to the computer. Other kinds of devices can be used to provide forinteraction with a user as well. For example, feedback provided to theuser can be any form of sensory feedback, e.g., visual feedback,auditory feedback, or tactile feedback; and input from the user can bereceived in any form, including acoustic, speech, or tactile input.

Embodiments of the subject matter described in this specification can beimplemented in a computing system that includes back end component(s)including one or more data servers, or that includes one or moremiddleware components such as application servers, or that includes afront end component such as a client computer having a graphical userinterface or a Web browser through which a user or administrator caninteract with some implementations of the subject matter described isthis specification, or any combination of one or more such back end,middleware, or front end components. The components of the system can beinterconnected by any form or medium of digital data communication, suchas a communication network. The computing system can include clients andservers. A client and server are generally remote from each other andtypically interact through a communication network. The relationship ofclient and server arises by virtue of computer programs running on therespective computers and having a client server relationship to eachother.

While this specification contains many specific implementation details,these should not be construed as limitations on the scope of anyinvention or of what may be claimed, but rather as descriptions offeatures that may be specific to particular embodiments of particularinventions. Certain features that are described in this specification inthe context of separate embodiments can also be implemented incombination in a single embodiment.

Conversely, various features that are described in the context of asingle embodiment can also be implemented in multiple embodimentsseparately or in any suitable subcombination. Moreover, althoughfeatures may be described above as acting in certain combinations andeven initially claimed as such, one or more features from a claimedcombination can in some cases be excised from the combination, and theclaimed combination may be directed to a subcombination or variation ofa subcombination.

Similarly, while operations are depicted in the drawings in a particularorder, this should not be understood as requiring that such operationsbe performed in the particular order shown or in sequential order, orthat all illustrated operations be performed, to achieve desirableresults. In certain circumstances, multitasking and parallel processingmay be advantageous. Moreover, the separation of various systemcomponents in the embodiments described above should not be understoodas requiring such separation in all embodiments, and it should beunderstood that the described program components and systems cangenerally be integrated together in a single software product orpackaged into multiple software products.

This written description sets forth the best mode of the invention andprovides examples to describe the invention and to enable a person ofordinary skill in the art to make and use the invention. This writtendescription does not limit the invention to the precise terms set forth.Thus, while the invention has been described in detail with reference tothe examples set forth above, those of ordinary skill in the art mayeffect alterations, modifications and variations to the examples withoutdeparting from the scope of the invention.

What is claimed is:
 1. A method, comprising: detecting, in a frame ofvideo rendered on a display of a television, a video content, includingat least detecting one or more graphics superimposed over a networkbroadcast of the video content; and transmitting, at least partially viathe Internet, at least one indication receivable by at least one contentrecognition operation, the at least one indication transmitted inresponse to detecting the video content including at least the detectedone or more graphics superimposed over the network broadcast of thevideo content, the transmitted at least one indication operable toassociate at least one of a “no match” result or an “on-screen graphicinterference” notification with one or more of at least some cue data orat least some fingerprint data related to video content being renderedon the display of the television.
 2. The method of claim 1, whereindetecting, in a frame of video rendered on a display of a television, avideo content, including at least detecting one or more graphicssuperimposed over a network broadcast of the video content comprises:detecting at least one graphic superimposed over the video content by atleast one of control logic associated with the television, an externaldevice operatively coupled with the television, or at least one of alocal broadcaster, satellite TV operator, or cable TV operatorretransmitting the content.
 3. The method of claim 1, wherein detecting,in a frame of video rendered on a display of a television, a videocontent, including at least detecting one or more graphics superimposedover a network broadcast of the video content comprises: detecting oneor more at least partially opaque graphics superimposed over the videocontent.
 4. The method of claim 1, wherein detecting, in a frame ofvideo rendered on a display of a television, a video content, includingat least detecting one or more graphics superimposed over a networkbroadcast of the video content comprises: detecting one or more of atleast one banner superimposed over the video content, at least onewatermark superimposed over the video content, or at least one logosuperimposed over the video content.
 5. The method of claim 1, whereindetecting, in a frame of video rendered on a display of a television, avideo content, including at least detecting one or more graphicssuperimposed over a network broadcast of the video content comprises:detecting one or more of at least some program guide information, atleast a portion of a graphical user interface, at least some programidentification information, at least some text, or at least some imagethat is not associated with original program content or underlying videoprogramming.
 6. The method of claim 1, wherein detecting, in a frame ofvideo rendered on a display of a television, a video content, includingat least detecting one or more graphics superimposed over a networkbroadcast of the video content comprises: detecting one or more highcontrast differences between sections of the video content.
 7. Themethod of claim 1, wherein detecting, in a frame of video rendered on adisplay of a television, a video content, including at least detectingone or more graphics superimposed over a network broadcast of the videocontent comprises: detecting the video content including one or moregraphics superimposed over the video content, including at least oneidentification of one or more of at least one horizontal edge, at leastone vertical edge, at least one diagonal edge, or at least one cornerassociated with the video content.
 8. The method of claim 7, whereindetecting the video content including one or more graphics superimposedover the video content, including at least one identification of one ormore of at least one horizontal edge, at least one vertical edge, atleast one diagonal edge, or at least one corner associated with thevideo content comprises: determining one or more pixel patch locationsand one or more pixel patch sizes corresponding with the one or morepixel patch locations; sampling at least some pixel data associated withthe video content, the sampling occurring at the one or more determinedpixel patch locations; transforming the at least some pixel data sampledfrom the one or more determined pixel patch locations; and identifyingone or more of at least one horizontal edge, at least one vertical edge,at least one diagonal edge, or at least one corner associated with thevideo content based at least partially on at least a portion of thetransformed at least some pixel data from at least one sampled pixelpatch.
 9. The method of claim 8, wherein sampling at least some pixeldata associated with the video content, the sampling occurring at theone or more determined pixel patch locations comprise: storing at leastone frame of the video content in one or more buffers; removing colordata associated with the video content from the one or more buffers;performing at least one Gaussian blur operation on the data in the oneor more buffers; and transforming data associated with the one or morepixel patch locations and the one or more buffers to identify one ormore high-contrast regions of pixel patches, the one or morehigh-contrast regions at least partially determinative of one or more ofat least one horizontal edge, at least one vertical edge, at least onediagonal edge, or at least one corner associated with the video content.10. The method of claim 9, wherein transforming data associated with theone or more pixel patch locations and the one or more buffers toidentify one or more high-contrast regions of pixel patches, the one ormore high-contrast regions at least partially determinative of one ormore of at least one horizontal edge, at least one vertical edge, atleast one diagonal edge, or at least one corner associated with thevideo content comprises: transforming data associated with the one ormore pixel patch locations and the one or more buffers using at leastone of a discrete cosine transform, a Sobel algorithm, a Sharralgorithm, or another algorithm operable to identify one or morehigh-contrast regions of pixel patches.
 11. The method of claim 8,further comprising: identifying one or more of at least one additionalhorizontal edge, at least one additional vertical edge, or at least oneadditional corner based at least partially on at least a portion of thetransformed at least some pixel data from at least one other sampledpixel patch.
 12. The method of claim 8, further comprising: identifyingone or more of at least one additional horizontal edge, at least oneadditional vertical edge, or at least one additional corner based atleast partially on one or more stepwise sweep operations, wherein astepwise sweep operation is configured for examining successive pixelpatch locations in at least one of a horizontal or vertical directionstarting from a pixel patch location associated with the identified oneor more of at least one horizontal edge, at least one vertical edge, orat least one corner.
 13. The method of claim 8, wherein determining oneor more pixel patch locations and one or more pixel patch sizescorresponding with the one or more pixel patch locations comprises:determining one or more pixel patch locations and one or more pixelpatch sizes corresponding with the one or more pixel patch locationsbased at least partially on at least one determination of at least oneresolution associated with the video content.
 14. The method of claim 1,wherein detecting, in a frame of video rendered on a display of atelevision, a video content, including at least detecting one or moregraphics superimposed over a network broadcast of the video contentcomprises: determining one or more pixel patch locations and one or morepixel patch sizes corresponding with the one or more pixel patchlocations; sampling at a first time at least some pixel data associatedwith the video content, the sampling occurring at the one or moredetermined pixel patch locations; sampling at a second time at leastsome pixel data associated with the video content, the samplingoccurring at the one or more determined pixel patch locations; andestablishing that at least one pixel patch is at least substantially thesame at both the first sample and the second sample and establishingthat at least one pixel patch substantially differs at the first sampleand the second sample.
 15. The method of claim 14, wherein establishingthat at least one pixel patch is at least substantially the same at boththe first sample and the second sample comprises: at least one of (i)establishing that at least one pixel patch is the same at both the firstsample and the second sample or (ii) establishing that at least aportion of the at least one pixel patch associated with one or more atleast partially opaque graphics is the same at both the first sample andthe second sample and establishing that an underlying portion of the atleast one pixel patch may vary between the first sample and the secondsample.
 16. The method of claim 14, wherein determining one or morepixel patch locations and one or more pixel patch sizes correspondingwith the one or more pixel patch locations comprises: determining one ormore pixel patch locations and one or more pixel patch sizescorresponding with the one or more pixel patch locations based at leastpartially on at least one determination of at least one resolutionassociated with the video content.
 17. The method of claim 1, whereindetecting, in a frame of video rendered on a display of a television, avideo content, including at least detecting one or more graphicssuperimposed over a network broadcast of the video content comprises:determining, via at least some data associated with the detecting avideo content, at least one resolution associated with the videocontent.
 18. The method of claim 17, wherein determining, via at leastsome data associated with the detecting a video content, at least oneresolution associated with the video content comprises: determining, viaat least some data associated with the detecting a video content, one ormore identifiers associated with the video content renderable in atleast one of HDTV or SDTV.
 19. The method of claim 1, wherein detecting,in a frame of video rendered on a display of a television, a videocontent, including at least detecting one or more graphics superimposedover a network broadcast of the video content comprises: receiving oneor more indications of one or more known graphics; and detecting one ormore graphics superimposed over the video content at least partiallybased on the received one or more indications of one or more knowngraphics.
 20. The method of claim 19, wherein receiving one or moreindications of one or more known graphics comprises: receiving at leastone of one (i) or more indications associated with one or morepreviously recognized watermarks or logos or (ii) one or moreindications associated with one or more banners or one or more userinterfaces implemented by one or more consumer electronic devices. 21.The method of claim 19, wherein receiving one or more indications of oneor more known graphics comprises: receiving the one or more indicationsat a client, the receiving at least one of (i) at manufacture of theclient, (ii) during a network update of the client, or (iii) during atleast one communication between the client and a system configured forat least determining one or more identifiers associated with the contentbeing rendered.
 22. The method of claim 19, wherein detecting one ormore graphics superimposed over the video content at least partiallybased on the received one or more indications of one or more knowngraphics comprises: detecting via at least some pixel pattern detectionwithin at least one proximity of one or more areas of a televisiondisplay known to be associated with locations of the received one ormore indications of one or more known graphics.
 23. The method of claim19, wherein detecting one or more graphics superimposed over the videocontent at least partially based on the received one or more indicationsof one or more known graphics comprises: detecting via at least somepixel pattern detection within at least one proximity of at least onecorner of a television display.
 24. The method of claim 19, whereindetecting one or more graphics superimposed over the video content atleast partially based on the received one or more indications of one ormore known graphics comprises: detecting one or more graphicssuperimposed over the video content at least partially based on thereceived one or more indications of one or more known graphics and basedat least partially on at least one determination of at least oneresolution associated with the content rendered on the display.
 25. Themethod of claim 19, wherein detecting one or more graphics superimposedover the video content at least partially based on the received one ormore indications of one or more known graphics comprises: detecting oneor more graphics superimposed over the video content at least one of asa part of a content recognition operation or following a previouscontent recognition operation.
 26. The method of claim 1, whereindetecting, in a frame of video rendered on a display of a television, avideo content, including at least detecting one or more graphicssuperimposed over a network broadcast of the video content comprises:detecting, by at least one of a widget of a smart television or a widgetof a consumer device coupled with a television, the one or more graphicssuperimposed over the video content.
 27. The method of claim 1, whereintransmitting, at least partially via the Internet, at least oneindication receivable by at least one content recognition operation, theat least one indication transmitted in response to detecting the videocontent including at least the detected one or more graphicssuperimposed over the network broadcast of the video content, thetransmitted at least one indication operable to associate at least oneof a “no match” result or an “on-screen graphic interference”notification with one or more of at least some cue data or at least somefingerprint data related to video content being rendered on the displayof the television comprises: transmitting one or more indicationsrelated to at least one of halting or resuming at least one processrelated to automated content recognition based at least partially on atleast one of a detection of one or more graphics superimposed over avideo content rendered on a display of a television or a detection of nographics superimposed over a video content rendered on a display of atelevision.
 28. The method of claim 27, wherein transmitting one or moreindications related to at least one of halting or resuming at least oneautomated content recognition process based at least partially on atleast one of a detection of one or more graphics superimposed over avideo content rendered on a display of a television or a detection of nographics superimposed over a video content rendered on a display of atelevision comprises transmitting the one or more indications to acentral system configured for at least determining one or moreidentifiers associated with content being rendered on a plurality oftelevisions.
 29. The method of claim 1, wherein transmitting, at leastpartially via the Internet, at least one indication receivable by atleast one content recognition operation, the at least one indicationtransmitted in response to detecting the video content including atleast the detected one or more graphics superimposed over the networkbroadcast of the video content, the transmitted at least one indicationoperable to associate at least one of a “no match” result or an“on-screen graphic interference” notification with one or more of atleast some cue data or at least some fingerprint data related to videocontent being rendered on the display of the television comprises:modifying at least one of one or more cues or one or more fingerprintsoperable to at least partially identify content being rendered, themodifying based at least partially on detecting the video contentincluding at least the detected one or more graphics superimposed overthe network broadcast of the video content.
 30. The method of claim 29,wherein modifying at least one of one or more cues or one or morefingerprints operable to at least partially identify content beingrendered, the modifying based at least partially on detecting the videocontent including at least the detected one or more graphicssuperimposed over the network broadcast of the video content comprises:determining at least some information related to at least one subset ofpixel patches associated with an automated content recognitionoperation, the automated content recognition operation based at leastpartially on a predefined number of pixel patches; and transmitting atleast one indication to at least one central system associated with theautomated content recognition operation related to the at least onesubset, the at least one indication operable to cause the automatedcontent recognition operation to attempt to recognize the content beingrendered based at least partially on the at least one subset of pixelpatches.
 31. The method of claim 29, wherein modifying at least one ofone or more cues or one or more fingerprints operable to at leastpartially identify content being rendered, the modifying based at leastpartially on detecting the video content including at least the detectedone or more graphics superimposed over the network broadcast of thevideo content comprises: determining at least some information relatedto at least one alternate set of pixel patches associated with anautomated content recognition operation, the automated contentrecognition operation based at least partially on at least onepredefined number of pixel patches, wherein the at least one alternateset of pixel patches is determined based at least partially on thedetected video content including one or more graphics; and transmittingat least one indication to at least one central system associated withthe automated content recognition operation related to the at least onesubset, the at least one indication operable to cause the automatedcontent recognition operation to attempt to recognize the content beingrendered based at least partially on the at least one alternate set ofpixel patches.
 32. The method of claim 1, wherein transmitting, at leastpartially via the Internet, at least one indication receivable by atleast one content recognition operation, the at least one indicationtransmitted in response to detecting the video content including atleast the detected one or more graphics superimposed over the networkbroadcast of the video content, the transmitted at least one indicationoperable to associate at least one of a “no match” result or an“on-screen graphic interference” notification with one or more of atleast some cue data or at least some fingerprint data related to videocontent being rendered on the display of the television comprises:transmitting at least one indication of at least one detection of atleast one video frame with one or more graphics superimposed overprogramming content associated with at least one video content beingrendered on the display of the television.
 33. The method of claim 1,further comprising: providing a television including at least: at leastone display capable of rendering received network broadcasts; at leastone processing device; at least one network connection; and at least onenon-transitory computer-readable medium including at least one or moreinstructions which, when executed on the at least one processing device,cause the at least one processing device to at least: detect the videocontent including at least detecting the one or more graphics; andtransmit, via the at least one network connection, the at least oneindication in response to detecting the video content including at leastdetecting the one or more graphics.
 34. The method of claim 33, whereinat least some of the one or more instructions, when executed on the atleast one processing device, cause the at least one processing device toat least: transmit, at least partially via the Internet and via the atleast one network connection, one or more of at least some fingerprintdata, at least some cue data, or at least one indication of one or morepixels renderable by the at least one display, the transmittingoccurring in at least one of real-time or near real-time, thetransmitting enabling a content recognition operation to utilize dataassociated with receiving the transmission to identify, in at least oneof real-time or near real-time, a program being rendered on thetelevision.
 35. The method of claim 1, wherein detecting, in a frame ofvideo rendered on a display of a television, a video content, includingat least detecting one or more graphics superimposed over a networkbroadcast of the video content comprises: detecting, in a frame of videoloaded into a display buffer at least one of prior to rendering theframe on the display, concurrent with rendering the frame on thedisplay, or subsequent to rendering the frame on the display, a videocontent, including at least detecting one or more graphics superimposedover a network broadcast of the video content.
 36. A computer programproduct, comprising: at least one non-transitory computer-readablemedium including at least: one or more instructions for detecting, in aframe of video rendered on a display of a television, a video content,including at least detecting one or more graphics superimposed over anetwork broadcast of the video content; and one or more instructions fortransmitting, at least partially via the Internet, at least oneindication receivable by at least one content recognition operation, theat least one indication transmitted in response to detecting the videocontent including at least the detected one or more graphicssuperimposed over the network broadcast in the superimposing operationoccurring subsequent to the network broadcast of the video content, thetransmitted at least one indication operable to associate at least oneof a “no match” result or an “on-screen graphic interference”notification with one or more of at least some cue data or at least somefingerprint data related to video content being rendered on the displayof the television.
 37. A system, comprising: circuitry configured fordetecting, in a frame of video rendered on a display of a television, avideo content, including at least detecting one or more graphicssuperimposed over a network broadcast of the video content; andcircuitry configured for transmitting, at least partially via theInternet, at least one indication receivable by at least one contentrecognition operation, the at least one indication transmitted inresponse to detecting the video content including at least the detectedone or more graphics superimposed over the network broadcast, thetransmitted at least one indication operable to associate at least oneof a “no match” result or an “on-screen graphic interference”notification with one or more of at least some cue data or at least somefingerprint data related to video content being rendered on the displayof the television.
 38. The system of claim 37, wherein circuitryconfigured for detecting, in a frame of video rendered on a display of atelevision, a video content, including at least detecting one or moregraphics superimposed over a network broadcast of the video contentcomprises: circuitry configured for detecting at least one graphicsuperimposed over the video content by at least one of control logicassociated with the television, an external device operatively coupledwith the television, or at least one of a local broadcaster, satelliteTV operator, or cable TV operator retransmitting the content.
 39. Thesystem of claim 37, wherein circuitry configured for detecting, in aframe of video rendered on a display of a television, a video content,including at least detecting one or more graphics superimposed over anetwork broadcast of the video content comprises: circuitry configuredfor detecting one or more of at least some program guide information, atleast a portion of a graphical user interface, at least some programidentification information, at least some text, or at least some imagethat is not associated with original program content or underlying videoprogramming.
 40. The system of claim 37, wherein circuitry configuredfor transmitting, at least partially via the Internet, at least oneindication receivable by at least one content recognition operation, theat least one indication transmitted in response to detecting the videocontent including at least the detected one or more graphicssuperimposed over the network broadcast of the video content, thetransmitted at least one indication operable to associate at least oneof a “no match” result or an “on-screen graphic interference”notification with one or more of at least some cue data or at least somefingerprint data related to video content being rendered on the displayof the television comprises: circuitry configured for transmitting atleast one indication of at least one detection of at least one videoframe with one or more graphics superimposed over programming contentassociated with at least one video content being rendered on the displayof the television.
 41. The system of claim 37, wherein circuitryconfigured for transmitting, at least partially via the Internet, atleast one indication receivable by at least one content recognitionoperation, the at least one indication transmitted in response todetecting the video content including at least the detected one or moregraphics superimposed over the network broadcast of the video content,the transmitted at least one indication operable to associate at leastone of a “no match” result or an “on-screen graphic interference”notification with one or more of at least some cue data or at least somefingerprint data related to video content being rendered on the displayof the television comprises: circuitry configured for transmitting oneor more indications related to at least one of halting or resuming atleast one process related to automated content recognition based atleast partially on at least one of a detection of one or more graphicssuperimposed over a video content rendered on a display of a televisionor a detection of no graphics superimposed over a video content renderedon a display of a television.
 42. The system of claim 37, wherein thecircuitry configured for detecting and the circuitry configured fortransmitting are at least partially implemented using at least oneprocessing device of the television or at least partially implementedusing at least one processing device of a client device coupled with thetelevision.